US9106366B2ActiveUtilityPatentIndex 52
Distributing data to multiple clients from server
Est. expiryDec 16, 2031(~5.5 yrs left)· nominal 20-yr term from priority
H04N 21/26613H04N 21/4753H04N 21/654H04N 21/25875H04N 21/4405H04L 9/0662H04L 2209/08H04N 21/8193H04N 21/2347H04L 9/00H04L 9/28
52
PatentIndex Score
0
Cited by
30
References
19
Claims
Abstract
Provided are techniques for distributing data in a trackable manner while suppressing an increase in the size of data to be distributed as much as possible and minimizing interruption of usage of the data. A method for distributing data to multiple clients from a server includes the steps of: generating a common noise by using noises unique to the multiple clients, respectively; embedding the common noise in the data to be distributed to make the data unusable; and distributing the data containing the embedded common noise, so that the data containing the embedded common noise is made usable by each of the multiple clients using a unique noise generated in the client.
Claims
exact text as granted — not AI-modifiedThe invention claimed is:
1. A method for distributing data to a plurality of clients from a server, the method comprising the steps of:
generating a common noise, the common noise being based on noises unique to respective ones of the plurality of clients;
embedding the common noise in the data to be distributed to the plurality of clients to make the data unusable; and
distributing the data containing the embedded common noise to the plurality of clients, so that the data containing the embedded common noise is made usable by each of the plurality of clients using a unique noise generated in the client;
wherein the unique noise is generated according to a given parameter; and
wherein the distributing step includes a step of sending the parameter, and the data containing the embedded common noise is made usable by each of the clients using the unique noise generated according to the parameter received by the client.
2. The method according to claim 1 , wherein the unique noise is a synthesis of a first noise and a second noise, the first noise having a larger amplitude than the second noise.
3. The method according to claim 1 , wherein the unique noise N(k,t) of a client k which is one of the plurality of clients is obtained according to the following formula:
N ( k,t )=αrand( t+s 0 )+βrand( t+s 1k )
where N(k,t) is the unique noise of client k, rand( )is random number generation function having very long cycle (T), t is a variable, α and β are coefficients such that α>1 and 0<β<<1, and s 0 and s 1k are seeds for client k.
4. The method according to claim 1 , wherein when the parameter is t 0 , the parameter t 0 is obtained according to the following formula:
t
0
=
arg
max
A
(
t
,
Δ
t
)
where
A
(
t
,
Δ
t
)
=
min
p
,
q
∈
D
,
p
≠
q
∫
t
t
+
Δ
t
(
N
(
p
,
t
)
-
N
(
q
,
t
)
)
ⅆ
t
where A is a minimum difference, t is a variable, Δt is the length in number of cycles) of noise necessary for embedding in content to be distributed, D is a set of clients included in distribution list, p,q is any combination of members in D, and N(q,t) is the unique noise of client k.
5. The method according to claim 1 , wherein distribution data including the parameter and the data containing the embedded common noise is sent to each of the plurality of distribution-target clients, the distribution data encrypted by using an encryption key unique to the client, and wherein each of the clients is provided with the parameter by decrypting the distribution data using a decryption key unique to the client.
6. The method according to claim 1 , wherein the generating step includes a step of calculating the mean of the unique noises of the plurality of clients, respectively.
7. The method according to claim 1 , wherein the server includes a mechanism for generating the unique noises of all the plurality of clients, and each of the plurality of clients includes a mechanism for generating its own unique noise.
8. The method according to claim 1 , wherein the data includes a variable-length code (VLC) portion, and the embedding step includes a step of changing the VLC portion included in the data based on the common noise.
9. The method according to claim 8 , wherein the changing step includes the steps of:
determining a map generated based on the common noise for a set of VLCs having an equal length; and
replacing a VLC in the data according to the map.
10. The method according to claim 9 , further comprising the steps of:
labeling members included in the set of equal-length codes; and
replacing a given VLC portion with a VLC corresponding to a label after replacement calculated according to the following formula:
L ′=( L−N p ( t ))mod c
where L′ is the label corresponding to VLC after replacement, L is the label corresponding to VLC before replacement, N p (t) is common noise, and c is a number of members in set of VLCs having certain length.
11. The method according to claim 8 , wherein the common noise is embedded in at least any of a DCT coefficient, a DC component, a macroblock pattern and a motion vector of the data.
12. The method according to claim 8 , wherein the changing step includes a step of changing a level of the VLC portion based on the common noise.
13. The method according to claim 12 , wherein the step of changing the level of the VLC portion includes a step of embedding information indicating in which direction, positive or negative, the level is changed.
14. The method according to claim 1 , wherein in the step of embedding the common noise, a common noise amplified or damped based on a predetermined coefficient is embedded in the data.
15. The method according to claim 14 , wherein when the unique noise of a client k which is one of the plurality of clients is N(k,t), the predetermined coefficient is determined by a function dependent on a variable t.
16. The method according to claim 1 , wherein the data to be distributed is data of a still image or video.
17. The method according to claim 1 , further comprising a step of receiving a distribution list D specifying a plurality of clients to which the data is to be distributed.
18. A non-transitory computer-readable storage medium comprising executable program code which, when executed by a processing device causes the processing device:
to generate a common noise, the common noise being based on noises unique to respective ones of a plurality of clients;
to embed the common noise in data to be distributed to the plurality of clients to make the data unusable; and
to distribute the data containing the embedded common noise to the plurality of clients, so that the data containing the embedded common noise is made usable by each of the plurality of clients using a unique noise generated in the client;
wherein the unique noise is generated according to a given parameter; and
wherein distributing the data containing the embedded noise comprises sending the parameter, and the data containing the embedded common noise is made usable by each of the clients using the unique noise generated according to the parameter received by the client.
19. A system for distributing data to a plurality of clients from a server, the system comprising:
at least one processing device comprising a processor coupled to a memory, the at least one processing device being configured:
to generate a common noise, the common noise being based on noises unique to respective ones of the plurality of clients;
to embed the common noise in the data to be distributed to the plurality of clients to make the data unusable; and
to distribute the data containing the embedded common noise to the plurality of clients, so that the data containing the embedded common noise is made usable by each of the plurality of clients using a unique noise generated in the client;
wherein the unique noise is generated according to a given parameter; and
wherein distributing the data containing the embedded noise comprises sending the parameter, and the data containing the embedded common noise is made usable by each of the clients using the unique noise generated according to the parameter received by the client.Cited by (0)
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